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Record W2158411091 · doi:10.1109/cecnet.2011.5769151

Verification and analysis of a TRNSYS model of a demonstration house equipped with a solar assisted ground coupled heat pump system

2011· article· en· W2158411091 on OpenAlexafffund
Chao Lü, Maoyu Zheng, Wey H. Leong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaScience and Technology Department, Heilongjiang ProvinceChina Scholarship CouncilDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsTRNSYSMoistureEnvironmental scienceLatent heatHeat transferHeat pumpPhase-change materialHeat exchangerThermalMeteorologyEngineeringMechanical engineeringMechanicsPhysics

Abstract

fetched live from OpenAlex

A TRNSYS model of a demonstration house equipped with a solar assisted ground coupled heat pump system (SAGCHPS) has been built. Besides using a built-in vertical ground heat exchanger (VGHE) module in TRNSYS, the model also uses a newly developed VGHE module which considers coupled heat and moisture transfer in ground with variable soil properties and phase change of soil moisture. The TRNSYS model with the new VGHE module (which has three simulation modes) is verified to produce better simulation results than the one with TRNSYS's built-in VGHE module, comparing with the field data of an actual and successful project. Coupled heat and moisture transfer effect in ground plays a more important role than variable soil properties and phase change of soil moisture. However, the result of considering all of them is the best. It is found that a simulation with pure heat transfer in ground (i.e., without moisture transfer and latent heat effect) can be considered in an early stage of a VGHE design. However, for better results and study of long-term effects, coupled heat and moisture transfer in ground with variable soil properties and phase change of soil moisture is recommended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.220
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2011
Admission routes2
Has abstractyes

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